Pattern detection generally aims to find previously unknown patterns in an input dataset. A pattern is an association of elements of the dataset that repeat throughout the duration of an examination time period. This is opposed to pattern matching methodologies, which look for matches in the input with pre-existing patterns, for example, using regular expressions.
Pattern detection methodologies require a significant amount of resources, e.g., computational resources and memory. When these resources are scarce or are otherwise unavailable, a pattern detection run may fail to complete analysis on input data.